Toward explainable artificial intelligence for precision pathology

F Klauschen, J Dippel, P Keyl… - Annual Review of …, 2024 - annualreviews.org
The rapid development of precision medicine in recent years has started to challenge
diagnostic pathology with respect to its ability to analyze histological images and …

Artificial intelligence for digital and computational pathology

AH Song, G Jaume, DFK Williamson, MY Lu… - Nature Reviews …, 2023 - nature.com
Advances in digitizing tissue slides and the fast-paced progress in artificial intelligence,
including deep learning, have boosted the field of computational pathology. This field holds …

High-plex immunofluorescence imaging and traditional histology of the same tissue section for discovering image-based biomarkers

JR Lin, YA Chen, D Campton, J Cooper, S Coy, C Yapp… - Nature cancer, 2023 - nature.com
Precision medicine is critically dependent on better methods for diagnosing and staging
disease and predicting drug response. Histopathology using hematoxylin and eosin (H&E) …

Validation of MSIntuit as an AI-based pre-screening tool for MSI detection from colorectal cancer histology slides

C Saillard, R Dubois, O Tchita, N Loiseau… - Nature …, 2023 - nature.com
Abstract Mismatch Repair Deficiency (dMMR)/Microsatellite Instability (MSI) is a key
biomarker in colorectal cancer (CRC). Universal screening of CRC patients for MSI status is …

A guide to artificial intelligence for cancer researchers

R Perez-Lopez, N Ghaffari Laleh, F Mahmood… - Nature Reviews …, 2024 - nature.com
Artificial intelligence (AI) has been commoditized. It has evolved from a specialty resource to
a readily accessible tool for cancer researchers. AI-based tools can boost research …

From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology

OSM El Nahhas, M van Treeck, G Wölflein, M Unger… - Nature …, 2024 - nature.com
Hematoxylin-and eosin-stained whole-slide images (WSIs) are the foundation of diagnosis
of cancer. In recent years, development of deep learning-based methods in computational …

Slideflow: deep learning for digital histopathology with real-time whole-slide visualization

JM Dolezal, S Kochanny, E Dyer, S Ramesh… - BMC …, 2024 - Springer
Deep learning methods have emerged as powerful tools for analyzing histopathological
images, but current methods are often specialized for specific domains and software …

[HTML][HTML] Mitosis detection, fast and slow: robust and efficient detection of mitotic figures

M Jahanifar, A Shephard, N Zamanitajeddin… - Medical Image …, 2024 - Elsevier
Counting of mitotic figures is a fundamental step in grading and prognostication of several
cancers. However, manual mitosis counting is tedious and time-consuming. In addition …

Open and reusable deep learning for pathology with WSInfer and QuPath

JR Kaczmarzyk, A O'Callaghan, F Inglis, S Gat… - NPJ Precision …, 2024 - nature.com
Digital pathology has seen a proliferation of deep learning models in recent years, but many
models are not readily reusable. To address this challenge, we developed WSInfer: an open …

[HTML][HTML] Artificial intelligence-based mitosis scoring in breast cancer: Clinical application

A Ibrahim, M Jahanifar, N Wahab, MS Toss… - Modern Pathology, 2024 - Elsevier
In recent years, artificial intelligence (AI) has demonstrated exceptional performance in
mitosis identification and quantification. However, the implementation of AI in clinical …